The Risk Association Between Blood Pb Levels and Diabetic Kidney Disease: A Cross-sectional Study Based on the NHANES Database 1999-2018

Background The onset of diabetic kidney disease (DKD) is insidious, with early symptoms not being obvious. When diagnosed, it often causes serious damage to the organism. The relationship between heavy metals and diabetic nephropathy (DKD), especially the threshold, has not been fully elucidated. Therefore, the aim of this study was to further investigate the association between environmental heavy metal exposure and the risk of DKD. Methods The National Health and Nutrition Examination Survey (NHANES) data from 1999 to 2018 were utilized for this study, comprising information on 1,343 participants. A baseline table was created to explore the differences in clinical characteristics between individuals with DKD and those without. Multivariate glm regression models were conducted to assess the correlation of clinical characteristics with DKD. Weighted logistic regression analysis was then employed to further confirm the stability of the correlation between exposure factors and DKD risk across populations. Finally, the independent predictive power of significantly differential clinical characteristics in DKD was explored using a nomogram. Meanwhile, the predictive accuracy of the nomogram was assessed. Results Clinical characteristics such as age, marital status, and serum Pb levels were significantly different between patients with diabetes mellitus (DM) with and without DKD. Serum Pb was identified as a risk factor correlated with DKD in three multivariate glm regression models (Model 1: odds ratio (OR) = 1.35, 95% confidence interval (CI): 1.18–1.54, p-value < 0.0001; Model 2: OR = 1.18, 95% CI: 1.05–1.34, p-value = 0.0060; Model 3: OR = 1.39, 95% CI: 1.19–1.61, p-value < 0.0001). After weighted logistic regression analysis, variables such as age, race, and PIR were also found to be associated with the risk of DKD. Based on these differential clinical characteristics, a nomogram was developed. Eventually, the area under the ROC curve was greater than 0.7, indicating a high degree of predictive accuracy. The calibration curve also demonstrated a good fit, and the decision curve analysis confirmed significant clinical benefit from using our nomogram. Conclusion The present study analyzsed data from the NHANES database and found a significant correlation between serum Pb levels and DKD, which had a non-linear relationship with a well-defined threshold.